Distributed multi-UAV trajectory optimization over directed networks

Liu, Tao; Han, Dongyu; Lin, Yeming; Liu, Kun

doi:10.1016/j.jfranklin.2021.04.044

Cited by 8 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Distributed algorithm (DA)-based cooperative mission assignment is computationally flexible, highly scalable, and can handle different levels of assignment separately, but the system's robustness decreases as the number of UAVs increases [10]. Liu et al [11] designed a mechanism to avoid UAV assignment conflicts and proposed a distributed adaptive algorithm based on individual and group decision making.…”

Section: Introductionmentioning

confidence: 99%

Multi-UAV Cooperative Mission Assignment Based on Hybrid WAFC-RRAS Algorithm

Huang,

Hu,

Yang

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Multi-UAV cooperative mission assignment is an important research direction in the field of UAV research. In the planning process, the assignment conflict between UAVs and mission points and the solution efficiency are the key difficulties in multi-UAV cooperative mission assignment. Based on the Weighted Approximate Flight Cost (WAFC) method and the Reduced Redundant Assignment Scheme (RRAS) algorithm, a multi-UAV cooperative mission problem considering different assignment models is proposed. The contributions of this study are: firstly, the approximate flight cost matrix is constructed based on the vertical distance between the UAV and the mission point, and the matrix is applied to calculate the initial flight distance of the UAV, which fully takes into account the effects of mountain type and radar threat on the mission assignment. Secondly, the auxiliary flight cost method and the spatial mapping matrix are constructed, which maps the discrete approximation of the flight cost to the continuous space and solves the UAV's local conflict problem in the assignment process. Finally, an adaptive selection mutation strategy based on iterative individual fitness values is proposed to reduce the redundancy of candidate assignment schemes and improve the efficiency of the planning system. The simulation results verify that the algorithm has high cooperative capability, good robustness and fast solution speed when dealing with cooperative multi-UAV mission assignment planning.INDEX TERMS Vertical cut method, Approximate flight cost method, Mapping strategies, Assignment conflicts, Multi-UAV cooperative mission assignment.

show abstract

Section: Introductionmentioning

confidence: 99%

Multi-UAV Cooperative Mission Assignment Based on Hybrid WAFC-RRAS Algorithm

Huang,

Hu,

Yang

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Through a literature survey, we found some relevant research papers. Tao Liu et al proposed a model-based distributed algorithm to minimize the energy consumption of the multi-UAV system, in which each UAV obtains its trajectory by solving the corresponding sub-problem, and the UAVs coordinate their trajectories according to the master problem [ 5 ]. Due to the application-specific nature of wireless sensor networks, Bhisham Sharma et al proposed a reliable and congestion-based protocol, which provides both bidirectional reliability and rate-adjustment-based congestion control [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Research on Aerial Autonomous Docking and Landing Technology of Dual Multi-Rotor UAV

Wang

Jiang²,

Wang³

et al. 2022

Sensors

View full text Add to dashboard Cite

This paper studies the cooperative control of multiple unmanned aerial vehicles (UAVs) with sensors and autonomous flight capabilities. In this paper, an architecture is proposed that takes a small quadrotor as a mission UAV and a large six-rotor as a platform UAV to provide an aerial take-off and landing platform and transport carrier for the mission UAV. The design of a tracking controller for an autonomous docking and landing trajectory system is the focus of this research. To examine the system’s overall design, a dual-machine trajectory-tracking control simulation platform is created via MATLAB/Simulink. Then, an autonomous docking and landing trajectory-tracking controller based on radial basis function proportional–integral–derivative control is designed, which fulfills the trajectory-tracking control requirements of the autonomous docking and landing process by efficiently suppressing the external airflow disturbance according to the simulation results. A YOLOv3-based vision pilot system is designed to calibrate the rate of the aerial docking and landing position to eight frames per second. The feasibility of the multi-rotor aerial autonomous docking and landing technology is verified using prototype flight tests during the day and at night. It lays a technical foundation for UAV transportation, autonomous take-off, landing in the air, and collaborative networking. In addition, compared with the existing technologies, our research completes the closed loop of the technical process through modeling, algorithm design and testing, virtual simulation verification, prototype manufacturing, and flight test, which have better realizability.

show abstract

“…This research offers a new paradigm for multi UAVs, one that makes distributed formation control operable across a wide range of MEC architectures, unlike previous work in [ 31 , 32 , 33 , 34 ]. Therefore, algorithms for optimal trajectory tracking, obstacle avoidance, and leader selection were incorporated into the resulting framework.…”

Section: Introductionmentioning

confidence: 99%

Path Planning and Formation Control for UAV-Enabled Mobile Edge Computing Network

Choutri

Lagha

Meshoul

et al. 2022

Sensors

View full text Add to dashboard Cite

Recent developments in unmanned aerial vehicles (UAVs) have led to the introduction of a wide variety of innovative applications, especially in the Mobile Edge Computing (MEC) field. UAV swarms are suggested as a promising solution to cope with the issues that may arise when connecting Internet of Things (IoT) applications to a fog platform. We are interested in a crucial aspect of designing a swarm of UAVs in this work, which is the coordination of swarm agents in complicated and unknown environments. Centralized leader–follower formations are one of the most prevalent architectural designs in the literature. In the event of a failed leader, however, the entire mission is canceled. This paper proposes a framework to enable the use of UAVs under different MEC architectures, overcomes the drawbacks of centralized architectures, and improves their overall performance. The most significant contribution of this research is the combination of distributed formation control, online leader election, and collaborative obstacle avoidance. For the initial phase, the optimal path between departure and arrival points is generated, avoiding obstacles and agent collisions. Next, a quaternion-based sliding mode controller is designed for formation control and trajectory tracking. Moreover, in the event of a failed leader, the leader election phase allows agents to select the most qualified leader for the formation. Multiple possible scenarios simulating real-time applications are used to evaluate the framework. The obtained results demonstrate the capability of UAVs to adapt to different MEC architectures under different constraints. Lastly, a comparison is made with existing structures to demonstrate the effectiveness, safety, and durability of the designed framework.

show abstract

Distributed multi-UAV trajectory optimization over directed networks

Cited by 8 publications

References 26 publications

Multi-UAV Cooperative Mission Assignment Based on Hybrid WAFC-RRAS Algorithm

Multi-UAV Cooperative Mission Assignment Based on Hybrid WAFC-RRAS Algorithm

Research on Aerial Autonomous Docking and Landing Technology of Dual Multi-Rotor UAV

Path Planning and Formation Control for UAV-Enabled Mobile Edge Computing Network

Contact Info

Product

Resources

About